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Introduction to Trading, Machine Learning & GCP に戻る

Google Cloud による Introduction to Trading, Machine Learning & GCP の受講者のレビューおよびフィードバック

3.9
495件の評価
141件のレビュー

コースについて

In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

人気のレビュー

MS

Jan 30, 2020

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

BA

Mar 16, 2020

Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.

フィルター:

Introduction to Trading, Machine Learning & GCP: 101 - 125 / 138 レビュー

by mohammadreza s

Feb 16, 2020

the platform they chose for submitting homework was not very well. most of the time it took me 15min to get to the platform to code the homework. also, it doesn't dig deep into topics, which is fine because it is a comprehensive course.

by Tiago C

Aug 16, 2020

The course has a few good points, but the lectures are often superficial. Also it seems like they are taking lectures from different courses and assembling them into one class, in a way that the lectures often seem disconnected.

by Nikolas M

Jan 14, 2020

Decent intro for ML but very limited in how it relates to trading. I would not say I feel comfortable creating an algo after this course. Also, felt very much like a Google ad quite often.

by rohit s

Jul 27, 2020

A decent introduction but with minimal hands on learning. Most of the initiative is on the student to learn about and apply the topics described here. Also tends to promote GCP a lot.

by Shekhar K

Jun 03, 2020

The course seems incomplete or not organized well. The concepts come and go out of nowhere. I knew lot of concepts beforehand and could figure out, but it was very fragmented.

by Chan W W K

Sep 01, 2020

The course is loosely organized. Some of the concepts in lab have not been gone through in the lecture. Anyway, the lectures presented by Jack is good.

by Andreas W

Sep 26, 2020

Theory of the financial part was interesting. "Coding" part was more or less running some fully implemented scripts from a github repository.

by Rustom F

Jan 30, 2020

The course seems to be more focused on advertising google cloud platform and there is hardly any focus on how to use ML or AI for trading.

by 欧阳坤

Jan 21, 2020

Too layman. NO real ML techniques for real trading, just some intro that you can easily find on stackoverflows or something.

by Rafiul H N

Jun 02, 2020

The course was great from Google's point but from the "New York Institute of Finance", it was confusing and not helpful.

by Pranesh

May 05, 2020

I expected to understand how we'd interact with the exchanges and then run mdeols in realtime for trading outcomes

by Pranav K S

Jan 27, 2020

This is a good introduction course, fourth week completely different or not aligned with course title.

by Konstantin K

Aug 31, 2020

So many words in that course and so little knowledge. For me, it was wasting time on 80%.

by Lazaris A

Mar 20, 2020

Nice theory very poor explaining in application not very useful to make you build a model

by Steve W

Dec 28, 2019

Some good parts, but several sections were cobbled together from other courses I've taken

by Hilmi E

Feb 01, 2020

The relationship between these three topics are somewhat loosely presented..

by Animesh

Jan 18, 2020

Not much learn from them, but whatever is there it's good.

by Jean-Luc B

Jan 11, 2020

Material sometimes seems like a patchwork in random order.

by Joe M

Apr 02, 2020

Good intro to concepts. Labs could use more thought.

by Alain T

Apr 04, 2020

Good Introduction to Time Series, ML and GCP!

by Bryan D

Jan 13, 2020

Ok as an introduction (it is what the title says after all), but I ended up doing a lot of things in the lab without really knowing why I was doing them (e.g. loading different libraries, a lot of the syntax, etc.). Granted I can research that on my own, but more guidance would have been appreciated.

More broadly, this course feels a bit chaotic, jumping from one topic to the other, and then getting back at a previous one. This is ok to explore the fundamentals, which is clearly the intent here, but more structure would be welcome. Particularly, the introduction to Jupyter notebooks coming at the end of the course, after three labs, feels a bit frustrating. On a similar note, the course really feels like (and clearly is) something that was patched together from bits and pieces of other courses, with often times instructors referring to "previous" topics that were not actually covered (e.g. random forests). For a paid specialisation, this feels a bit sub-par. I have had free Coursera courses that felt more consistant.

by Sam F

Jan 03, 2020

Had I not read another book on ML, I probably wouldn't understand a lot of material covered here. The course might be a good recap if you already know the material. However for someone who is new to ML, the videos just dumps a lot of definition on you without real explanation in layman term. I ended up having to go to other YouTube videos for explanation.

by Oleksandr S

Feb 02, 2020

The course gives you a very limited introduction to ML for trading. More examples of time series models, basic trading strategies, use of ML methods etc are needed.

by Jonathan S

Sep 13, 2020

Actual programming was nonexistent, the assignments just had you run already-written jupyter notebooks

by Michael K

Jan 23, 2020

Lacks depth of most topics , too brief of an introduction